Lecture 11. Parameter estimation and maximum likelihood

Statistical Data Analysis

Dmitry V. Naumov (JINR)

Draft Outline

• TODO: likelihood function and estimators
• TODO: bias, consistency, efficiency
• TODO: profile likelihood and constraints

Exercises

Exercise

Show that the likelihood for a Poisson count \(n\) with expectation \(\mu\) is \[ L(\mu)=\frac{\mu^n e^{-\mu}}{n!}. \]